Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem

Jun He, Yong Wang, Yuren Zhou

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

2 Citations (SciVal)
133 Downloads (Pure)

Abstract

Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation and
greedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.
Original languageEnglish
Title of host publicationEvolutionary Computation in Combinatorial Optimization
EditorsGabriela Ochoa
PublisherSpringer Nature
Pages74-85
Volume9026
ISBN (Electronic)978-3-319-16468-7
ISBN (Print)978-3-319-16467-0, 3319164678
DOIs
Publication statusPublished - 15 Mar 2015

Publication series

NameLecture notes in Computer Science
Volume9026

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